IBM SPSS Modeler Foundations (V18.2)
- Kursuskode 0A069G
- Varighed 2 dage
Leveringsmetoder
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Leveringsmetoder
Kurset er tilgængeligt i følgende formater:
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Åbent kursus
Traditionel klasserumsundervisning
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Åbent kursus (Virtuelt)
Live klasserumsundervisning du tilgår virtuelt
Anmod om dette kursus Med en anden leveringsløsning
Beskrivelse
ToppenThis course provides the foundations of using IBM SPSS Modeler and introduces the participant to data science. The principles and practice of data science are illustrated using the CRISP-DM methodology. The course provides training in the basics of how to import, explore, and prepare data with IBM SPSS Modeler v18.2, and introduces the student to modeling.
Virtuel deltagelse
Et V&C Select kursus indholder nøjagtig det samme som et almindeligt kursus. Før kursusstart modtager man kursusmaterialet. Dernæst logger man på kurset via internettet og ser via sin pc den selvsamme præsentation som de øvrige deltagere, man kommunikerer via chat med underviseren og de øvrige deltagere på kurset. Denne uddannelsesmodel er både tids-og omkostningsbesparende og kan være et oplagt alternativ til almindelig klasseundervisning, hvis man f.eks. har et begrænset rejsebudget.
Kursusdato
Toppen-
- Leveringsmetode: Åbent kursus (Virtuelt)
- Dato: 25 august, 2025
- Kursussted: Virtual
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- Leveringsmetode: Åbent kursus (Virtuelt)
- Dato: 10-11 november, 2025
- Kursussted: Virtual
Målgruppe
Toppen- Data scientists
- Business analysts
- Clients who are new to IBM SPSS Modeler or want to find out more about using it
Kursets formål
ToppenAt the end of the course, participants will be able to :
- Collect initial data
- Understand data
- Define the unit of analysis
- Integrate data
- Transform fields
- Examine the relationship between a categorical field and a continuous field
- Discover modeling
- Improving efficiency
Kursusindhold
Toppen- Introduction to IBM SPSS Modeler
- Introduction to data science
- Describe the CRISP-DM methodology
- Introduction to IBM SPSS Modeler
- Build models and apply them to new data
- Collect initial data
- Describe field storage
- Describe field measurement level
- Import from various data formats
- Export to various data formats
- Understand the data
- Audit the data
- Check for invalid values
- Take action for invalid values
- Define blanks
- Set the unit of analysis
- Remove duplicates
- Aggregate data
- Transform nominal fields into flags
- Restructure data
- Integrate data
- Append datasets
- Merge datasets
- Sample records
- Transform fields
- Use the Control Language for Expression Manipulation
- Derive fields
- Reclassify fields
- Bin fields
- Further field transformations
- Use functions
- Replace field values
- Transform distributions
- Examine relationships
- Examine the relationship between two categorical fields
- Examine the relationship between a categorical and continuous field
- Examine the relationship between two continuous fields
- Introduction to modeling
- Describe modeling objectives
- Create supervised models
- Create segmentation models
- Improve efficiency
- Use database scalability by SQL pushback
- Process outliers and missing values with the Data
- Audit node
- Use the Set Globals node
- Use parameters
- Use looping and conditional execution
Forudsætninger
Toppen- Knowledge of your business requirements
- Basic understanding of Data Science
Mere information
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